Overview

Dataset statistics

Number of variables12
Number of observations81
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory92.8 B

Variable types

NUM11
CAT1

Reproduction

Analysis started2020-07-25 00:15:40.016038
Analysis finished2020-07-25 00:16:46.901176
Duration1 minute and 6.89 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

FRENTE AMPLIO is highly correlated with UNIDAD SOCIAL CRISTIANA and 1 other fieldsHigh correlation
UNIDAD SOCIAL CRISTIANA is highly correlated with FRENTE AMPLIO and 4 other fieldsHigh correlation
LIBERACIÓN NACIONAL is highly correlated with UNIDAD SOCIAL CRISTIANA and 5 other fieldsHigh correlation
MOVIMIENTO LIBERTARIO is highly correlated with UNIDAD SOCIAL CRISTIANA and 4 other fieldsHigh correlation
ALIANZA PATRIÓTICA is highly correlated with MOVIMIENTO LIBERTARIO and 1 other fieldsHigh correlation
ACCIÓN CIUDADANA is highly correlated with LIBERACIÓN NACIONAL and 1 other fieldsHigh correlation
ACCESIBILIDAD SIN EXCLUSIÓN is highly correlated with UNIDAD SOCIAL CRISTIANA and 3 other fieldsHigh correlation
NULOS is highly correlated with UNIDAD SOCIAL CRISTIANA and 4 other fieldsHigh correlation
BLANCOS is highly correlated with NULOSHigh correlation
PROVINCIA Y CANTÓN has unique values Unique
LIBERACIÓN NACIONAL has unique values Unique
ACCIÓN CIUDADANA has unique values Unique

Variables

PROVINCIA Y CANTÓN
Categorical

UNIQUE

Distinct count81
Unique (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
PALMARES
 
1
MORAVIA
 
1
BAGACES
 
1
POCOCÍ
 
1
FLORES
 
1
Other values (76)
76
ValueCountFrequency (%) 
PALMARES11.2%
 
MORAVIA11.2%
 
BAGACES11.2%
 
POCOCÍ11.2%
 
FLORES11.2%
 
LIBERIA11.2%
 
AGUIRRE11.2%
 
PARAÍSO11.2%
 
PUNTARENAS11.2%
 
VÁZQUEZ DE CORONADO11.2%
 
Other values (71)7187.7%
 
2020-07-24T18:16:47.117806image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length19
Median length8
Mean length8.222222222
Min length3

UNIDAD SOCIAL CRISTIANA
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count80
Unique (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean914.9876543209876
Minimum99.0
Maximum6436.000000000007
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:47.388001image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum99
5-th percentile210
Q1360
median575
Q31062
95-th percentile2816
Maximum6436
Range6337
Interquartile range (IQR)702

Descriptive statistics

Standard deviation972.1046175
Coefficient of variation (CV)1.062423753
Kurtosis13.5410821
Mean914.9876543
Median Absolute Deviation (MAD)273
Skewness3.181784007
Sum74114
Variance944987.3873
2020-07-24T18:16:48.141017image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
45922.5%
 
47411.2%
 
44411.2%
 
66111.2%
 
46611.2%
 
36611.2%
 
51011.2%
 
179211.2%
 
22611.2%
 
35911.2%
 
Other values (70)7086.4%
 
ValueCountFrequency (%) 
9911.2%
 
13611.2%
 
14211.2%
 
19011.2%
 
21011.2%
 
ValueCountFrequency (%) 
643611.2%
 
386811.2%
 
371111.2%
 
286111.2%
 
281611.2%
 

INTEGRACIÓN NACIONAL
Real number (ℝ≥0)

Distinct count40
Unique (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.296296296296298
Minimum2
Maximum202
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:48.362870image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q16
median14
Q325
95-th percentile79
Maximum202
Range200
Interquartile range (IQR)19

Descriptive statistics

Standard deviation35.36185955
Coefficient of variation (CV)1.3979066
Kurtosis12.13845457
Mean25.2962963
Median Absolute Deviation (MAD)8
Skewness3.266452947
Sum2049
Variance1250.461111
2020-07-24T18:16:48.609919image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1456.2%
 
456.2%
 
556.2%
 
656.2%
 
344.9%
 
844.9%
 
1144.9%
 
933.7%
 
1033.7%
 
1733.7%
 
Other values (30)4049.4%
 
ValueCountFrequency (%) 
222.5%
 
344.9%
 
456.2%
 
556.2%
 
656.2%
 
ValueCountFrequency (%) 
20211.2%
 
17911.2%
 
14211.2%
 
9711.2%
 
7911.2%
 

ALIANZA PATRIÓTICA
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count51
Unique (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.98765432098765
Minimum5.0
Maximum164.0
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:48.799934image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8
Q117
median29
Q347
95-th percentile97
Maximum164
Range159
Interquartile range (IQR)30

Descriptive statistics

Standard deviation32.40852273
Coefficient of variation (CV)0.8312508997
Kurtosis3.893340378
Mean38.98765432
Median Absolute Deviation (MAD)16
Skewness1.824369456
Sum3158
Variance1050.312346
2020-07-24T18:16:49.010287image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1367.4%
 
1056.2%
 
4733.7%
 
2233.7%
 
2033.7%
 
2133.7%
 
2733.7%
 
833.7%
 
3633.7%
 
2422.5%
 
Other values (41)4758.0%
 
ValueCountFrequency (%) 
522.5%
 
833.7%
 
1056.2%
 
1111.2%
 
1211.2%
 
ValueCountFrequency (%) 
16411.2%
 
15911.2%
 
12311.2%
 
10111.2%
 
9711.2%
 

RENOVACIÓN COSTARRICENSE
Real number (ℝ≥0)

Distinct count76
Unique (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172.1604938271605
Minimum8
Maximum941
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:49.597738image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile17
Q168
median109
Q3218
95-th percentile543
Maximum941
Range933
Interquartile range (IQR)150

Descriptive statistics

Standard deviation183.4732581
Coefficient of variation (CV)1.06571057
Kurtosis5.508421641
Mean172.1604938
Median Absolute Deviation (MAD)65
Skewness2.257622121
Sum13945
Variance33662.43642
2020-07-24T18:16:49.851877image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
22222.5%
 
6922.5%
 
9122.5%
 
1422.5%
 
5422.5%
 
82011.2%
 
17811.2%
 
5311.2%
 
17411.2%
 
94111.2%
 
Other values (66)6681.5%
 
ValueCountFrequency (%) 
811.2%
 
1311.2%
 
1422.5%
 
1711.2%
 
2111.2%
 
ValueCountFrequency (%) 
94111.2%
 
82011.2%
 
69511.2%
 
68211.2%
 
54311.2%
 

FRENTE AMPLIO
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count66
Unique (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.7283950617284
Minimum3.0
Maximum618.0000000000007
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:50.050152image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6
Q118
median51
Q3104
95-th percentile306
Maximum618
Range615
Interquartile range (IQR)86

Descriptive statistics

Standard deviation102.1053393
Coefficient of variation (CV)1.219482819
Kurtosis9.779344924
Mean83.72839506
Median Absolute Deviation (MAD)39
Skewness2.749263913
Sum6782
Variance10425.50031
2020-07-24T18:16:50.272465image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
5133.7%
 
933.7%
 
622.5%
 
522.5%
 
4022.5%
 
4322.5%
 
3722.5%
 
1222.5%
 
1122.5%
 
2622.5%
 
Other values (56)5972.8%
 
ValueCountFrequency (%) 
311.2%
 
522.5%
 
622.5%
 
711.2%
 
811.2%
 
ValueCountFrequency (%) 
61811.2%
 
39111.2%
 
33711.2%
 
33511.2%
 
30611.2%
 

LIBERACIÓN NACIONAL
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct count81
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11068.098765432098
Minimum1307.0
Maximum70913.00000000007
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:50.560114image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum1307
5-th percentile2250
Q14264
median6626
Q313403
95-th percentile29625
Maximum70913
Range69606
Interquartile range (IQR)9139

Descriptive statistics

Standard deviation11825.37308
Coefficient of variation (CV)1.068419548
Kurtosis10.04882174
Mean11068.09877
Median Absolute Deviation (MAD)3502
Skewness2.875674853
Sum896516
Variance139839448.6
2020-07-24T18:16:51.259122image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1651911.2%
 
1804611.2%
 
1340311.2%
 
856911.2%
 
1841511.2%
 
4029811.2%
 
462611.2%
 
456911.2%
 
303511.2%
 
261711.2%
 
Other values (71)7187.7%
 
ValueCountFrequency (%) 
130711.2%
 
136111.2%
 
164211.2%
 
211811.2%
 
225011.2%
 
ValueCountFrequency (%) 
7091311.2%
 
5469711.2%
 
4576011.2%
 
4029811.2%
 
2962511.2%
 

MOVIMIENTO LIBERTARIO
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count80
Unique (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4935.6543209876545
Minimum355
Maximum27992
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:51.566200image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum355
5-th percentile731
Q11873
median3641
Q35578
95-th percentile14738
Maximum27992
Range27637
Interquartile range (IQR)3705

Descriptive statistics

Standard deviation5157.11813
Coefficient of variation (CV)1.044870202
Kurtosis8.853417769
Mean4935.654321
Median Absolute Deviation (MAD)1792
Skewness2.73680863
Sum399788
Variance26595867.4
2020-07-24T18:16:51.767235image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
184922.5%
 
371111.2%
 
2769011.2%
 
374311.2%
 
579311.2%
 
1347411.2%
 
425911.2%
 
144411.2%
 
54911.2%
 
323911.2%
 
Other values (70)7086.4%
 
ValueCountFrequency (%) 
35511.2%
 
54911.2%
 
68411.2%
 
71911.2%
 
73111.2%
 
ValueCountFrequency (%) 
2799211.2%
 
2769011.2%
 
1853911.2%
 
1640011.2%
 
1473811.2%
 

ACCIÓN CIUDADANA
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct count81
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5912.061728395061
Minimum339.0
Maximum40882.0
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:51.970845image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum339
5-th percentile556
Q11579
median3068
Q36808
95-th percentile19077
Maximum40882
Range40543
Interquartile range (IQR)5229

Descriptive statistics

Standard deviation7109.84351
Coefficient of variation (CV)1.202599674
Kurtosis7.97244127
Mean5912.061728
Median Absolute Deviation (MAD)1802
Skewness2.575201655
Sum478877
Variance50549874.73
2020-07-24T18:16:52.289138image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2388611.2%
 
427011.2%
 
80711.2%
 
201511.2%
 
55611.2%
 
58811.2%
 
1146711.2%
 
221611.2%
 
129011.2%
 
306811.2%
 
Other values (71)7187.7%
 
ValueCountFrequency (%) 
33911.2%
 
43811.2%
 
46311.2%
 
53311.2%
 
55611.2%
 
ValueCountFrequency (%) 
4088211.2%
 
2720911.2%
 
2670611.2%
 
2388611.2%
 
1907711.2%
 

ACCESIBILIDAD SIN EXCLUSIÓN
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count77
Unique (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean445.7283950617284
Minimum22
Maximum3194
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:53.078148image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile30
Q1131
median248
Q3591
95-th percentile1279
Maximum3194
Range3172
Interquartile range (IQR)460

Descriptive statistics

Standard deviation570.7411193
Coefficient of variation (CV)1.280468388
Kurtosis9.973768946
Mean445.7283951
Median Absolute Deviation (MAD)178
Skewness2.894566332
Sum36104
Variance325745.4253
2020-07-24T18:16:53.270363image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
14022.5%
 
3022.5%
 
24822.5%
 
13522.5%
 
18211.2%
 
16811.2%
 
234411.2%
 
4211.2%
 
17211.2%
 
5111.2%
 
Other values (67)6782.7%
 
ValueCountFrequency (%) 
2211.2%
 
2411.2%
 
2611.2%
 
3022.5%
 
3211.2%
 
ValueCountFrequency (%) 
319411.2%
 
278111.2%
 
234411.2%
 
153811.2%
 
127911.2%
 

NULOS
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count78
Unique (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean401.91358024691357
Minimum33
Maximum2023
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:53.478518image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile68
Q1146
median287
Q3485
95-th percentile1126
Maximum2023
Range1990
Interquartile range (IQR)339

Descriptive statistics

Standard deviation382.4279408
Coefficient of variation (CV)0.9515178378
Kurtosis5.759647514
Mean401.9135802
Median Absolute Deviation (MAD)155
Skewness2.248002395
Sum32555
Variance146251.1299
2020-07-24T18:16:53.855111image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
20322.5%
 
28722.5%
 
12822.5%
 
5611.2%
 
18511.2%
 
17411.2%
 
5011.2%
 
107511.2%
 
18011.2%
 
56611.2%
 
Other values (68)6884.0%
 
ValueCountFrequency (%) 
3311.2%
 
5011.2%
 
5611.2%
 
6611.2%
 
6811.2%
 
ValueCountFrequency (%) 
202311.2%
 
181011.2%
 
153211.2%
 
129111.2%
 
112611.2%
 

BLANCOS
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count63
Unique (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.91358024691358
Minimum9.0
Maximum293.0
Zeros0
Zeros (%)0.0%
Memory size648.0 B
2020-07-24T18:16:54.341107image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile22
Q139
median68
Q3107
95-th percentile237
Maximum293
Range284
Interquartile range (IQR)68

Descriptive statistics

Standard deviation65.07729972
Coefficient of variation (CV)0.7574739585
Kurtosis1.763789389
Mean85.91358025
Median Absolute Deviation (MAD)33
Skewness1.481039247
Sum6959
Variance4235.054938
2020-07-24T18:16:54.803837image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2944.9%
 
2233.7%
 
7133.7%
 
5522.5%
 
4822.5%
 
3422.5%
 
6022.5%
 
4322.5%
 
11722.5%
 
9222.5%
 
Other values (53)5770.4%
 
ValueCountFrequency (%) 
911.2%
 
1611.2%
 
1911.2%
 
2233.7%
 
2411.2%
 
ValueCountFrequency (%) 
29311.2%
 
27911.2%
 
25811.2%
 
24311.2%
 
23711.2%
 

Interactions

2020-07-24T18:15:57.084188image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:15:57.681275image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:15:58.000178image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:15:58.827140image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:15:59.023284image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:15:59.250093image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:15:59.501837image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:00.498316image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:00.914902image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:01.263130image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:02.000998image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:02.235433image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:02.475650image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:02.719114image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:02.972829image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:03.831232image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:04.071665image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:04.305240image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:04.516378image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:05.375888image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:05.782238image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:06.024802image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:06.454073image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:07.215984image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:07.513881image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:07.824077image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:08.653124image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:09.186748image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:09.452918image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:10.158829image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:10.405907image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:10.651240image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:10.879304image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:11.084911image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:11.776983image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
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2020-07-24T18:16:44.621164image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Correlations

2020-07-24T18:16:55.080196image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-07-24T18:16:55.569994image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-07-24T18:16:56.468798image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-07-24T18:16:56.940161image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-07-24T18:16:45.302843image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2020-07-24T18:16:46.445070image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Sample

First rows

PROVINCIA Y CANTÓNUNIDAD SOCIAL CRISTIANAINTEGRACIÓN NACIONALALIANZA PATRIÓTICARENOVACIÓN COSTARRICENSEFRENTE AMPLIOLIBERACIÓN NACIONALMOVIMIENTO LIBERTARIOACCIÓN CIUDADANAACCESIBILIDAD SIN EXCLUSIÓNNULOSBLANCOS
0SAN JOSÉ6436.0179164.0941618.070913.02769040882.031942023293.0
1ESCAZÚ688.02131.011592.014627.059796427.059134551.0
2DESAMPARADOS3711.0202123.0543337.045760.01853926706.023441532198.0
3PURISCAL640.01136.06440.09127.030674086.024821394.0
4TARRAZÚ351.01714.03017.03263.012661737.08712250.0
5ASERRÍ945.07824.0122113.011430.049776560.0603425108.0
6MORA488.0719.07837.05815.025512810.024823464.0
7GOICOECHEA1945.014258.0401306.025171.01051219077.01279768105.0
8SANTA ANA761.01422.013159.09605.042144494.036523271.0
9ALAJUELITA1294.02536.0214107.012914.068016201.0100048477.0

Last rows

PROVINCIA Y CANTÓNUNIDAD SOCIAL CRISTIANAINTEGRACIÓN NACIONALALIANZA PATRIÓTICARENOVACIÓN COSTARRICENSEFRENTE AMPLIOLIBERACIÓN NACIONALMOVIMIENTO LIBERTARIOACCIÓN CIUDADANAACCESIBILIDAD SIN EXCLUSIÓNNULOSBLANCOS
71COTO BRUS374.01132.05442.06958.033943068.0163395101.0
72PARRITA235.0612.01129.03214.01849463.04215339.0
73CORREDORES463.0840.018365.06257.037063260.016147992.0
74GARABITO302.028.01412.02827.01248533.0309722.0
75LIMÓN1838.05880.0520125.014045.099086889.0716932237.0
76POCOCÍ1472.05092.0820239.017254.0164008475.08281291219.0
77SIQUIRRES1062.01640.0379172.09717.053512511.0322631107.0
78TALAMANCA988.01423.012540.03473.017751998.056292116.0
79MATINA806.01469.045743.04851.034171266.0105414117.0
80GUÁCIMO474.01641.022263.05874.048822082.024148586.0